Wireless communication systems using multiple-input multiple-output (MIMO) multiplexing are known. According to MIMO, a transmission signal transmitted by a transmitter device contains a result of multiplexing a plurality of independent symbols. The receiver device receives the transmitted signal via a plurality of reception antennas, demodulates the reception signal, and outputs soft-decision data corresponding to the transmitted bits. In the MIMO demodulation, the receiver device performs the process of estimating the optimal symbols from the reception signal.
Exemplary known approaches for estimating the optimal symbol from a reception signal include full-maximum likelihood detection (MLD), which searches for the nearest lattice point comprehensively for every symbol, and, maximum mean square estimation (MMSE). Another known approach for reducing the computational load of the Full-MLD is complexity reduced MLD with QR decomposition and M-algorithm (QRM-MLD).
It is known that, the probability at which a symbol nearer to the optimal symbol is detected can be improved by applying linear detection such as MMSE under a lattice-reduced basis that is resultant of lattice reduction transformation, compared with when linear detection is applied under the original basis. Furthermore, it is known that reception characteristics such as an error ratio are improved under certain conditions by applying QRM-MLD under the lattice-reduced basis that is resultant of the lattice reduction transformation.
Prior art examples are disclosed in D. Wubben, R. Bohnke, V. Kuhn, and K. D. Kammeyer, “Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction,” IEEE Int. Conf. on Commun. (ICC '04), Vol. 2, June, 2004; X.-F. Qi and K. Holt, “A Lattice-Reduction-Aided Soft Demapper for High-Rate Coded MIMO-OFDM Systems” IEEE Signal Processing Letters, vol. 14, no. 5, pp. 305-308, May 2007; and S. Aubert, Y. Nasser, and F. Nouvel, “Lattice Reduction-Aided Minimum Mean Square Error K-Best Detection for MIMO Systems” in International Conference on Computing, Networking and Communications, ICNC 2012.
A transmitter device appends an error-correcting code and the like, and transmits the resultant information bit sequence, as an encoded bit sequence. The receiver device then demodulates the received signal sequence, generates soft-decision data, and performs processing such as error correction based on the generated soft-decision data, and estimates the transmitted information bit sequence. While QRM-MLD is capable of reducing the computational load by applying the lattice reduction, the computational load is still quite heavy, compared with linear detection such as MMSE.
In addition, linear detection using the lattice reduction outputs hard-decision data as the demodulation result. Linear detection using the lattice reduction is capable of achieving an error-correction performance equivalent to that of QRM-MLD with the lattice reduction, but with less computational load than that in QRM-MLD using the lattice reduction. Considering subsequent processes including error correction using the soft-decision data, linear detection using the lattice reduction, however, exhibits inferior reception performance, compared with QRM-MLD using the lattice reduction.